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Moving Object Detection Using Tensor-Based Low-Rank and Saliently Fused-Sparse Decomposition
Hu, Wenrui; Yang, Yehui; Zhang, Wensheng; Xie, Yuan
Source PublicationIEEE TRANSACTIONS ON IMAGE PROCESSING
2017-02-01
Volume26Issue:2Pages:724-737
SubtypeArticle
AbstractIn this paper, we propose a new low-rank and sparse representation model for moving object detection. The model preserves the natural space-time structure of video sequences by representing them as three-way tensors. Then, it operates the low-rank background and sparse foreground decomposition in the tensor framework. On the one hand, we use the tensor nuclear norm to exploit the spatio-temporal redundancy of background based on the circulant algebra. On the other, we use the new designed saliently fused-sparse regularizer (SFS) to adaptively constrain the foreground with spatio-temporal smoothness. To refine the existing foreground smooth regularizers, the SFS incorporates the local spatio-temporal geometric structure information into the tensor total variation by using the 3D locally adaptive regression kernel (3D-LARK). What is more, the SFS further uses the 3D-LARK to compute the space-time motion saliency of foreground, which is combined with the l(1) norm and improves the robustness of foreground extraction. Finally, we solve the proposed model with globally optimal guarantee. Extensive experiments on challenging well-known data sets demonstrate that our method significantly outperforms the state-of-the-art approaches and works effectively on a wide range of complex scenarios.
KeywordMoving Object Detection Tensor Nuclear Norm Tensor Total Variation Space-time Visual Saliency
WOS HeadingsScience & Technology ; Technology
DOI10.1109/TIP.2016.2627803
WOS KeywordBACKGROUND SUBTRACTION ; VISUAL SURVEILLANCE ; REGULARIZATION ; FRAMEWORK ; RECOVERY ; ROBUST ; IMAGE
Indexed BySCI
Language英语
Funding OrganizationNational Natural Science Foundation of China(61402480 ; 61432008 ; 61472423 ; 61502495 ; 61532006)
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS IDWOS:000404773100010
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Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/15244
Collection精密感知与控制研究中心_人工智能与机器学习
AffiliationChinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Hu, Wenrui,Yang, Yehui,Zhang, Wensheng,et al. Moving Object Detection Using Tensor-Based Low-Rank and Saliently Fused-Sparse Decomposition[J]. IEEE TRANSACTIONS ON IMAGE PROCESSING,2017,26(2):724-737.
APA Hu, Wenrui,Yang, Yehui,Zhang, Wensheng,&Xie, Yuan.(2017).Moving Object Detection Using Tensor-Based Low-Rank and Saliently Fused-Sparse Decomposition.IEEE TRANSACTIONS ON IMAGE PROCESSING,26(2),724-737.
MLA Hu, Wenrui,et al."Moving Object Detection Using Tensor-Based Low-Rank and Saliently Fused-Sparse Decomposition".IEEE TRANSACTIONS ON IMAGE PROCESSING 26.2(2017):724-737.
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